{"id":3706258,"url":"https://alion.io/job/campbell-global-software-engineer-iii-aiml-developer","title":"Software Engineer III - AI/ML Developer","company":{"id":2649833,"name":"Campbell Global","domain":"campbellglobal.com","url":"https://alion.io/company/campbellglobal","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Oracle","truth_index":{"grade":"A","score":94,"open_postings":144,"ghost_share":0.069,"stale_share":0.201,"repost_share":0.125,"time_to_fill_p50_days":13,"computed_at":"2026-11-03T05:54:40Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"middle","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Plano, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"Amazon SageMaker","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"GCP","optional":false},{"name":"Machine Learning","optional":false},{"name":"Pandas","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Scikit-learn","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"TensorFlow","optional":false},{"name":"CloudFormation","optional":true},{"name":"Databricks","optional":true},{"name":"Docker","optional":true},{"name":"Feature Store","optional":true},{"name":"Kubernetes","optional":true},{"name":"Rest API","optional":true},{"name":"Snorkel","optional":true},{"name":"Snowflake","optional":true},{"name":"Terraform","optional":true}],"status":"live","first_seen_at":"2026-11-03T18:54:12Z","employer_posted_date":"2026-11-03","last_verified_at":"2026-11-04T00:58:00Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.\nAs a Software Engineer III at JPMorganChase within the Consumer & Community Banking, you are part of an agile team that works to enhance, design, and deliver the software components of the firm’s state-of-the-art technology products in a secure, stable, and scalable way. As an emerging member of a software engineering team, you execute software solutions through the design, development, and technical troubleshooting of multiple components within a technical product, application, or system, while gaining the skills and experience needed to grow within your role.\nJob responsibilities:\nExecutes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problems\nDevelops secure and high-quality production code, and reviews and debugs code written by others\nDrives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.\nApplies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.\nIdentifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems\nLeads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture\nDesigns, develops, codes, and troubleshoots with consideration of upstream and downstream systems and technical implications\nApplies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation\nApplies technical troubleshooting to breakdown solutions and solve technical problems of basic complexity\nGathers, analyzes, and draws conclusions from large, diverse data sets to identify problems and contribute to decision-making in service of secure, stable application development\nLearns and applies system processes, methodologies, and skills for the development of secure, stable code and systems\nRequired qualifications, capabilities, and skills:\nFormal training or certification on software engineering concepts and 3+ years applied experience\nHands-on practical experience delivering system design, application development, testing, and operational stability\nHands-on experience building, deploying, and maintaining machine learning platforms or infrastructure\nProficiency in Python and one or more ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). Experience with data processing frameworks and tools (e.g., Spark, Pandas, SQL) \nPractical experience with cloud-based ML platforms (e.g., AWS SageMaker, GCP AI Platform, Azure ML) or on-prem ML infrastructure\nDemonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.\nStrong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices\nProficient in all aspects of the Software Development Life Cycle\nAdvanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security\nIn-depth knowledge of the financial services industry and their IT systemsPractical cloud native experience\n\nPreferred qualifications, capabilities, and skills:\nFamiliarity with Databricks for scalable data engineering and ML platform integration\nExperience working with Snowflake for cloud-based data warehousing and analytics\nExposure to Snorkel AI for programmatic data labeling and training data management\nExperience with containerization and orchestration tools (e.g., Docker, Kubernetes, Airflow)\nFamiliarity with feature stores, model registries, and ML metadata management\nExperience with infrastructure-as-code tools (e.g., Terraform, CloudFormation)\nExperience with RESTful APIs and microservices 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